With the development of the Internet, users obtain a variety of information from various information communication equipments anywhere and anytime. For example, users often read various types of information using various information communication equipments such as smart phone, smart pad, notebook, and desktop PC.
Recently, data storage media have been increased in capacity and reduced in price, and Internet connection techniques have been diversified and increased in speed. Accordingly, users encounter an enormous quantity of contents. Furthermore, general users as well as large contents providers provide various contents based on fundamental techniques such as Blog, SNS (Social Networking Service), Twitter, and Internet Cafes. That is, as anyone may provide information and contents anywhere and anytime, contents are gradually becoming huge.
Therefore, precision and recall of information retrieval have become further important. For example, techniques such as Semantic Web are used for retrieving information and generating new contents. Semantic Web enables a computer to read, understand, and process information instead of a person.
Yet, the information retrieval (or contents retrieval) has been centered around contents providers. That is because, when a user inputs a search word into a search window of a portal site or the like, current information retrieval systems filter and extract information based on the user's search word.
In such information retrieval systems, users should repeat a retrieval operation several times, in order to acquire contents containing information desired by the users. Sometimes, although users spare a large amount of time for contents retrieval, the users may not acquire desired contents, but should pay for using the Internet. This is because, although the users want to read specific and professional contents, information retrieval systems do not actively deal with users' requests.